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ds000007-mriqc: "Expected dimension is 4D and you provided a 3D image" #46

Closed jbwexler closed 1 year ago

jbwexler commented 1 year ago

Just for sub-18. I suspect it may have to do with the T1w https://openneuro.org/datasets/ds000007/versions/00001/file-display/sub-18:anat:sub-18_T1w.nii.gz

Node: mriqc_wf.funcMRIQC.ICA Working directory: /scratch1/03201/jbwexler/work_dir/mriqc/ds000007_sub-18/mriqc_wf/funcMRIQC/_infile..scratch1..03201..jbwexler..openneuro_derivatives..derivatives..mriqc..ds000007-mriqc..sourcedata..raw..sub-18..func..sub-18_task-stopvocal_run-1_bold.nii.gz/ICA

Node inputs:

ICs = approach = args = bg_image = bg_threshold = compress_report = False cov_weight = dim = dim_est = environ = {'FSLOUTPUTTYPE': 'NIFTI_GZ'} epsilon = epsilonS = in_files = log_power = mask = max_restart = maxit = migp = migpN = migp_factor = migp_shuffle = mix = mm_thresh = no_bet = True no_mask = True no_mm = True non_linearity = num_ICs = out_all = out_dir = out_mean = out_orig = out_pca = out_report = melodic_reportlet.svg out_stats = out_unmix = out_white = output_type = NIFTI_GZ pbsc = rem_cmp = remove_deriv = report = report_maps = report_mask = s_con = s_des = sep_vn = sep_whiten = smode = t_con = t_des = tr_sec = update_mask = var_norm =

Traceback (most recent call last): File "/opt/conda/lib/python3.8/site-packages/nipype/pipeline/plugins/multiproc.py", line 67, in run_node result["result"] = node.run(updatehash=updatehash) File "/opt/conda/lib/python3.8/site-packages/nipype/pipeline/engine/nodes.py", line 516, in run result = self._run_interface(execute=True) File "/opt/conda/lib/python3.8/site-packages/nipype/pipeline/engine/nodes.py", line 635, in _run_interface return self._run_command(execute) File "/opt/conda/lib/python3.8/site-packages/nipype/pipeline/engine/nodes.py", line 741, in _run_command result = self._interface.run(cwd=outdir) File "/opt/conda/lib/python3.8/site-packages/nipype/interfaces/base/core.py", line 429, in run runtime = self._post_run_hook(runtime) File "/opt/conda/lib/python3.8/site-packages/niworkflows/interfaces/reportlets/segmentation.py", line 169, in _post_run_hook self._generate_report() File "/opt/conda/lib/python3.8/site-packages/niworkflows/interfaces/reportlets/segmentation.py", line 184, in _generate_report plot_melodic_components( File "/opt/conda/lib/python3.8/site-packages/niworkflows/viz/utils.py", line 637, in plot_melodic_components for i, img in enumerate(iter_img(os.path.join(melodic_dir, "melodic_IC.nii.gz"))): File "/opt/conda/lib/python3.8/site-packages/nilearn/image/image.py", line 696, in iter_img return check_niimg_4d(imgs, return_iterator=True) File "/opt/conda/lib/python3.8/site-packages/nilearn/_utils/niimg_conversions.py", line 379, in check_niimg_4d return check_niimg(niimg, ensure_ndim=4, return_iterator=return_iterator, File "/opt/conda/lib/python3.8/site-packages/nilearn/_utils/niimg_conversions.py", line 296, in check_niimg raise DimensionError(len(niimg.shape), ensure_ndim) nilearn._utils.exceptions.DimensionError: Input data has incompatible dimensionality: Expected dimension is 4D and you provided a 3D image. See http://nilearn.github.io/manipulating_images/input_output.html.

jbwexler commented 1 year ago

This seems to have been fixed in newer versions of mriqc.